{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": [
     "remove-cell"
    ]
   },
   "outputs": [],
   "source": [
    "import sys\n",
    "import os\n",
    "if not any(path.endswith('textbook') for path in sys.path):\n",
    "    sys.path.append(os.path.abspath('../../..'))\n",
    "from textbook_utils import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": [
     "remove-cell"
    ]
   },
   "outputs": [],
   "source": [
    "import plotly.figure_factory as ff"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Example: Wind-Damaged Trees \n",
    "\n",
    "In 1999, a huge storm with winds over 90 mph damaged millions of trees in the [Boundary Waters Canoe Area Wilderness](https://www.fs.usda.gov/visit/destination/boundary-waters-canoe-area-wilderness) (BWCAW), which has the largest tract of virgin forest in the eastern US. In an effort to understand the susceptibility of trees to wind damage, a researcher named [Roy Lawrence Rich](https://www.proquest.com/docview/305463532?pq-origsite=gscholar&fromopenview=true) carried out a ground survey of the BWCAW. In the years following this study, other researchers have used this dataset to model _windthrow_, or the uprooting of trees in strong winds."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The population under study are the trees in the BWCAW. The access frame are *transects*: straight lines that cut through the natural landscape. These particular transects begin close to a lake and travel orthogonal to the gradient of the land for 250–400 meters. Along these transects, surveyors stop every 25 meters and examine a 5-by-5-meter plot. At each plot, trees are counted, categorized as blown down or standing, measured in diameter at 6 ft from the ground, and their species recorded. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Sampling protocols like this are common for studying natural resources. In the BWCAW, over 80% of the land in the region is within 500 meters of a lake, so the access frame nearly covers the population. The study took place over the summers of  2000 and 2001, and no other natural disasters happened between the 1999 storm and when the data were collected. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Measurements were collected on over 3,600 trees, but in this example, we examine just the black spruce. There are over 650 of them. We read in these data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>diameter</th>\n",
       "      <th>storm</th>\n",
       "      <th>status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>9.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>standing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11.0</td>\n",
       "      <td>0.03</td>\n",
       "      <td>standing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9.0</td>\n",
       "      <td>0.03</td>\n",
       "      <td>standing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>656</th>\n",
       "      <td>9.0</td>\n",
       "      <td>0.94</td>\n",
       "      <td>fallen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>657</th>\n",
       "      <td>17.0</td>\n",
       "      <td>0.94</td>\n",
       "      <td>fallen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>658</th>\n",
       "      <td>8.0</td>\n",
       "      <td>0.98</td>\n",
       "      <td>fallen</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>659 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     diameter  storm    status\n",
       "0         9.0   0.02  standing\n",
       "1        11.0   0.03  standing\n",
       "2         9.0   0.03  standing\n",
       "..        ...    ...       ...\n",
       "656       9.0   0.94    fallen\n",
       "657      17.0   0.94    fallen\n",
       "658       8.0   0.98    fallen\n",
       "\n",
       "[659 rows x 3 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trees = pd.read_csv('data/black_spruce.csv')\n",
    "trees"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Each row corresponds to a single tree and has the following attributes:\n",
    "\n",
    "`diameter`\n",
    ": Diameter of the tree in cm, measured at 6 ft above the ground \n",
    "`storm`\n",
    ": Severity of the storm (fraction of trees that fell in a 25-meter-wide area containing the tree)\n",
    "`status`\n",
    ": Tree has \"fallen\" or is \"standing\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's begin with some exploratory analysis before we turn to modeling. First, we calculate some simple summary statistics:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
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       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>diameter</th>\n",
       "      <th>storm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>5.0</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>6.0</td>\n",
       "      <td>0.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>8.0</td>\n",
       "      <td>0.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>12.0</td>\n",
       "      <td>0.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>32.0</td>\n",
       "      <td>0.98</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     diameter  storm\n",
       "min       5.0   0.02\n",
       "25%       6.0   0.21\n",
       "50%       8.0   0.36\n",
       "75%      12.0   0.55\n",
       "max      32.0   0.98"
      ]
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trees.describe()[3:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Based on the quartiles, the distribution of tree diameter seems skewed right. Let's compare  the distribution of diameter for the standing and fallen trees with histograms:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
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font-size: 14px; fill: rgb(36, 36, 36); opacity: 1; font-weight: normal; white-space: pre;\">Fallen tree diameter (cm)</text></g><g class=\"g-x2title\"><text class=\"x2title\" x=\"472.32500000000005\" y=\"239.70625\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(36, 36, 36); opacity: 1; font-weight: normal; white-space: pre;\">Standing tree diameter (cm)</text></g><g class=\"g-ytitle\" transform=\"translate(4.9873046875,0)\"><text class=\"ytitle\" transform=\"rotate(-90,10.012500000000003,100.5)\" x=\"10.012500000000003\" y=\"100.5\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(36, 36, 36); opacity: 1; font-weight: normal; white-space: pre;\">density</text></g><g class=\"g-y2title\"/></g></svg>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f1 = px.histogram(trees.query('status == \"fallen\"'), x=\"diameter\", \n",
    "                  histnorm='probability density', nbins = 30)\n",
    "f2 = px.histogram(trees.query('status == \"standing\"'), x=\"diameter\", \n",
    "                  histnorm='probability density')\n",
    "\n",
    "fig = left_right(f1, f2, height=250, width=600)\n",
    "fig.update_xaxes(title_text='Fallen tree diameter (cm)', \n",
    "                 row=1, col=1, range=[3, 35])\n",
    "fig.update_xaxes(title_text='Standing tree diameter (cm)', \n",
    "                 row=1, col=2, range=[3, 35])\n",
    "fig.update_yaxes(title_text='density', row=1, col=1)\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The distribution of the diameter of the trees that fell in the storm is centered at 12 cm with a right skew. In comparison, the standing trees were nearly all under 10 cm in diameter with a mode at about 6 cm (only trees with a diameter of at least 5 cm are included in the study). \n",
    "\n",
    "Another feature to investigate is the strength of the storm. We plot the storm strength against the tree diameter using the symbol and marker color to distinguish the standing trees from the fallen ones. Since the diameter is essentially measured to the nearest cm, many trees have the same diameter, so we jitter the values by adding a bit of noise to the diameter values to help reduce overplotting (see {numref}`Chapter %s <ch:viz>`). We also adjust the opacity of the marker colors to reveal the denser regions on the plot: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": [
     "hide-input"
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   "outputs": [],
   "source": [
    "def jitter(data, amt=0.2):\n",
    "    return data + amt * (np.random.rand(len(data)) - 0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
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   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-04-02T16:07:17.773256Z",
     "start_time": "2018-04-02T16:07:17.757563Z"
    },
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = px.scatter(\n",
    "    trees, x=jitter(trees[\"diameter\"], amt=0.5), y=\"storm\",\n",
    "    color=\"status\", symbol=\"status\",\n",
    "    log_x=True, width=650, height=300,\n",
    ")\n",
    "\n",
    "fig.update_traces(marker=dict(opacity=0.6, size=5))\n",
    "\n",
    "fig.update_layout(\n",
    "    xaxis_title=\"Tree diameter (cm)\",\n",
    "    yaxis_title=\"Local strength of storm\",\n",
    "    legend_title=\"Tree status\",\n",
    ")\n",
    "\n",
    "fig"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From this plot, it looks like both the tree diameter and the strength of the storm are related to windthrow: whether the tree was uprooted or left standing. Notice that windthrow, the feature we want to predict, is a nominal variable. In the next section, we consider how this impacts the prediction problem."
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " "
   ]
  }
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